The present specification describes a system for diagnosing or screening one or more pathologies in a patient. The system includes a headset with at least one microphone or accelerometer to passively receive vibrations generated by the cerebral vasculature of the patient's brain, computing devices coupled with the headset for processing the received vibrations to obtain a unique signal, and a signal analyzer to analyze the signal in order to determine if the data includes patterns uniquely indicative of at least one of tension headaches, migraines, depression, dementia, Alzheimer's disease, epilepsy, Parkinson's disease, autism, cerebral vasospasm and meningitis.

Provided herein are methods of obtaining and applying measurements of metabolites to quantifying maternal risk of having a child with autism spectrum disorder (ASD), with high specificity and sensitivity.

A method of determining a parameter related to a blood oxygenation of tissue may include projecting an optical pattern onto the issue, the optical pattern comprising a spatially varying component in at least one axis. A method of determining a parameter related to a blood oxygenation of tissue may include collecting a reflected optical signal from at least a first and a second wavelength range, wherein the first and the second wavelength ranges are distinct. A method of determining a parameter related to a blood oxygenation of tissue may include normalizing the reflected optical signal. A method of determining a parameter related to a blood oxygenation of tissue may include performing a transform of the reflected optical signal. A method of determining a parameter related to a blood oxygenation of tissue may include determining the parameter related to the blood oxygenation of the tissue based on the ratio and the transform.

System and methods for identifying a brain condition of a patient subject to a plurality of disease states are provided, in some aspects, the method includes receiving imaging data associated with a patient's brain acquired using an imaging system, and constructing a classifier having signatures corresponding to a plurality of disease states. The method also includes applying the classifier to the imaging data to determine a degree to which the patient expresses at least one of the plurality of disease states, and determining a brain condition of the patient using the determined degree. The method further includes generating a report indicative of the brain condition of the patient.

A brain-function image data augmentation method includes: a step of providing a target database including a plurality of image-data information; a step of, based on a plurality of image-data expected information in an expectation-value database, calculating a ratio of the plurality of image-data expected information with respect to different ages; a step of, based on the plurality of image-data information and the ratio, obtaining image-data ratio information with respect to an estimated age; a step of establishing a relationship for each pair of the image-data information and the image-data expected information; a step of, based on the relationship, the ratio and the image-data information, calculating an estimated image-data information with respect to the estimated age; and, a step of combining linearly the estimated image-data information and the image-data ratio information so as to generate an augmented image-data information with respect to the estimated age.

An image including contrast is standardized and an area is divided, a measurement cross section that most matches a measurement cross section determined to be appropriate for measuring a predetermined index is determined based on a feature of a notable tissue in the divided area, and a measurement value serving as an index is calculated in the measurement cross section.

Methods, systems, and computer-readable media are disclosed herein for predictive, diagnostic, and therapeutic applications of wearables for mental health. Information is received from at least one user device comprising a wearable device and corresponding to a user of the at least one user device. A response from the user to a validating questionnaire for a type of mental disorder or neurological disorder is received. A risk score corresponding to the type of mental disorder or neurological disorder and based at least in part on the information and the response to the validating questionnaire is determined. A determination is made as to whether the risk score is within a first predetermined range. In response to the risk score not being within the first predetermined range, a notification is automatically provided. Feedback from the wearable device is received in response to the user taking a medication prescribed after automatically providing the notification. The feedback indicates data corresponding to an activity or a behavior of the user is not within a second predetermined range. A follow up is automatically scheduled in response to receiving the feedback.

An eye-movement data acquisition system includes an illumination source configured to produce infrared light and a camera assembly configured to receive a portion of the infrared light reflected from a user's face during activation of the infrared illumination source. The camera assembly includes a rolling shutter sensor configured to produce individual scan line images associated with the user's eyes at a line sampling rate. A processor is communicatively coupled to the camera assembly and the illumination sources and is configured to produce eye-movement data based on the individual scan line images.

A dexterity testing apparatus includes a housing and a sensor. The housing is configured to be manipulated with digits of one hand of a user. The sensor is supported by the housing and configured to generate user dexterity data based upon changes in acceleration and orientation of the housing as the housing moves relative to the digits of the one hand of the user. The sensor is configured to convert the user dexterity data into an output signal indicative of the user's dexterity.

An imaging-based biomarker that indicates a neurological state of a subject is generated from magnetic resonance imaging data acquired from the subject while the subject was sleeping, or during both a sleep state and wake state. These magnetic resonance imaging data are acquired in such a way so that they simultaneously enable measurement of cerebrospinal fluid (“CSF”) flow and blood-oxygenation-level dependent (“BOLD”) signals. The imaging-based biomarker can be generated based on a correlation between CSF signals and BOLD signals extracted from these magnetic resonance imaging data. Using electroencephalography (“EEG”) data, CSF flow dynamics can also be estimated based on a physiological model in which coherent neural activity is modeled as entraining oscillations in blood volume and CSF.